airweave
Open-source context retrieval layer for AI agents
Stars: 5698
Airweave is an open-core tool that simplifies the process of making data searchable by unifying apps, APIs, and databases into a vector database with minimal configuration. It offers over 120 integrations, simplicity in syncing data from diverse sources, extensibility through 'sources', 'destinations', and 'embedders', and an async-first approach for large-scale data synchronization. With features like no-code setup, white-labeled multi-tenant support, chunk generators, automated sync, versioning & hashing, multi-source support, and scalability, Airweave provides a comprehensive solution for building applications that require semantic search.
README:
Open-source context retrieval layer for AI agents and RAG systems.
Airweave connects to your apps, tools, and databases, continuously syncs their data, and exposes it through a unified, LLM-friendly search interface. AI agents query Airweave to retrieve relevant, grounded, up-to-date context from multiple sources in a single request.
Airweave sits between your data sources and AI systems as shared retrieval infrastructure. It handles authentication, ingestion, syncing, indexing, and retrieval so you don't have to rebuild fragile pipelines for every agent or integration.
- Connect your apps, databases, and documents (50+ integrations)
- Airweave syncs, indexes, and exposes your data through a unified retrieval layer
- Agents query Airweave via our SDKs, REST API, MCP, or native integrations with popular agent frameworks
- Agents retrieve relevant, grounded context on demand
Cloud-hosted: app.airweave.ai
git clone https://github.com/airweave-ai/airweave.git
cd airweave
./start.shRequires Docker and docker-compose
pip install airweave-sdk # Python
npm install @airweave/sdk # TypeScriptfrom airweave import AirweaveSDK
client = AirweaveSDK(api_key="YOUR_API_KEY")
results = client.collections.search(
readable_id="my-collection",
query="Find recent failed payments"
)- Frontend: React/TypeScript with ShadCN
- Backend: FastAPI (Python)
- Databases: PostgreSQL (metadata), Qdrant (vectors)
- Workers: Temporal (orchestration), Redis (pub/sub)
- Deployment: Docker Compose (dev), Kubernetes (prod)
We welcome contributions! See our Contributing Guide.
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